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Found 6 papers, 1 papers with code
Real-Time Cell Sorting with Scalable In Situ FPGA-Accelerated Deep Learning
This framework provides a scalable, cost-effective solution for lymphocyte classification, as well as a new SOTA real-time cell sorting implementation for rapid identification of subsets using in situ deep learning on off-the-shelf computing hardware.
Taming Gradient Variance in Federated Learning with Networked Control Variates
To address this, we introduce a novel Networked Control Variates (FedNCV) framework for Federated Learning.
MIML: Multiplex Image Machine Learning for High Precision Cell Classification via Mechanical Traits within Microfluidic Systems
MIML has been proven effective in classifying white blood cells and tumor cells, with potential for broader application due to its inherent flexibility and transfer learning capability.
Coarse-Grained Molecular Simulation of Extracellular Vesicles Squeezing for Drug Loading
Effective loading of exogenous cargos without compromising the extracellular vesicle membrane is a major challenge.
Stacked Generative Machine Learning Models for Fast Approximations of Steady-State Navier-Stokes Equations
Computational fluid dynamics (CFD) simulations are broadly applied in engineering and physics.
Applications and Techniques for Fast Machine Learning in Science
In this community review report, we discuss applications and techniques for fast machine learning (ML) in science -- the concept of integrating power ML methods into the real-time experimental data processing loop to accelerate scientific discovery.
